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  <div class="section" id="numpy-core-records-fromrecords">
<h1>numpy.core.records.fromrecords<a class="headerlink" href="#numpy-core-records-fromrecords" title="Permalink to this headline">¶</a></h1>
<dl class="function">
<dt id="numpy.core.records.fromrecords">
<code class="sig-prename descclassname">numpy.core.records.</code><code class="sig-name descname">fromrecords</code><span class="sig-paren">(</span><em class="sig-param">recList</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">shape=None</em>, <em class="sig-param">formats=None</em>, <em class="sig-param">names=None</em>, <em class="sig-param">titles=None</em>, <em class="sig-param">aligned=False</em>, <em class="sig-param">byteorder=None</em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/v1.18.1/numpy/core/records.py#L648-L714"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#numpy.core.records.fromrecords" title="Permalink to this definition">¶</a></dt>
<dd><p>create a recarray from a list of records in text form</p>
<blockquote>
<div><p>The data in the same field can be heterogeneous, they will be promoted
to the highest data type.  This method is intended for creating
smaller record arrays.  If used to create large array without formats
defined</p>
<p>r=fromrecords([(2,3.,’abc’)]*100000)</p>
<p>it can be slow.</p>
<p>If formats is None, then this will auto-detect formats. Use list of
tuples rather than list of lists for faster processing.</p>
</div></blockquote>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">r</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">core</span><span class="o">.</span><span class="n">records</span><span class="o">.</span><span class="n">fromrecords</span><span class="p">([(</span><span class="mi">456</span><span class="p">,</span><span class="s1">&#39;dbe&#39;</span><span class="p">,</span><span class="mf">1.2</span><span class="p">),(</span><span class="mi">2</span><span class="p">,</span><span class="s1">&#39;de&#39;</span><span class="p">,</span><span class="mf">1.3</span><span class="p">)],</span>
<span class="gp">... </span><span class="n">names</span><span class="o">=</span><span class="s1">&#39;col1,col2,col3&#39;</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="nb">print</span><span class="p">(</span><span class="n">r</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="go">(456, &#39;dbe&#39;, 1.2)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">r</span><span class="o">.</span><span class="n">col1</span>
<span class="go">array([456,   2])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">r</span><span class="o">.</span><span class="n">col2</span>
<span class="go">array([&#39;dbe&#39;, &#39;de&#39;], dtype=&#39;&lt;U3&#39;)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="kn">import</span> <span class="nn">pickle</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">pickle</span><span class="o">.</span><span class="n">loads</span><span class="p">(</span><span class="n">pickle</span><span class="o">.</span><span class="n">dumps</span><span class="p">(</span><span class="n">r</span><span class="p">))</span>
<span class="go">rec.array([(456, &#39;dbe&#39;, 1.2), (  2, &#39;de&#39;, 1.3)],</span>
<span class="go">          dtype=[(&#39;col1&#39;, &#39;&lt;i8&#39;), (&#39;col2&#39;, &#39;&lt;U3&#39;), (&#39;col3&#39;, &#39;&lt;f8&#39;)])</span>
</pre></div>
</div>
</dd></dl>

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